Submission¶

Put the ipynb file and html file in the github branch you created in the last assignment and submit the link to the commit in brightspace

In [1]:
from plotly.offline import init_notebook_mode
import plotly.io as pio
import plotly.express as px

init_notebook_mode(connected=True)
pio.renderers.default = "plotly_mimetype+notebook"
In [2]:
#load data
df = px.data.gapminder()
df.head()
Out[2]:
country continent year lifeExp pop gdpPercap iso_alpha iso_num
0 Afghanistan Asia 1952 28.801 8425333 779.445314 AFG 4
1 Afghanistan Asia 1957 30.332 9240934 820.853030 AFG 4
2 Afghanistan Asia 1962 31.997 10267083 853.100710 AFG 4
3 Afghanistan Asia 1967 34.020 11537966 836.197138 AFG 4
4 Afghanistan Asia 1972 36.088 13079460 739.981106 AFG 4

Question 1:¶

Recreate the barplot below that shows the population of different continents for the year 2007.

Hints:

  • Extract the 2007 year data from the dataframe. You have to process the data accordingly
  • use plotly bar
  • Add different colors for different continents
  • Sort the order of the continent for the visualisation. Use axis layout setting
  • Add text to each bar that represents the population
In [3]:
df = px.data.gapminder()

#Sorting the population for the year 2007
df_2007 = df.query('year==2007')

#Grouping them by continents and summing the values to get full bar

df_2007_new = df_2007.groupby('continent').sum()
fig = px.bar(df_2007_new, x="pop", y=df_2007_new.index, orientation='h',
             color = df_2007_new.index,
             text_auto=True,#Showing the population value 
             #you can also use string formatting to round off values (text_auto='0.2s')
)

#Sorting the y axis in ascending order
fig.update_yaxes(categoryorder = 'max ascending')

fig.show()

Question 2:¶

Sort the order of the continent for the visualisation

Hint: Use axis layout setting

In [4]:
df = px.data.gapminder()

df_2007 = df.query('year==2007')

df_2007_new = df_2007.groupby('continent').sum()
fig = px.bar(df_2007_new, x="pop", y=df_2007_new.index, orientation='h',
             color = df_2007_new.index,
             
)

fig.update_yaxes(categoryorder = 'max ascending')

fig.show()

Question 3:¶

Add text to each bar that represents the population

In [5]:
df = px.data.gapminder()
df_2007_new = df_2007.groupby('continent').sum()
fig = px.bar(df_2007_new, x="pop", y=df_2007_new.index, orientation='h',
             color = df_2007_new.index,
             text_auto=True,#Showing the population value 
             #you can also use string formatting to round off values (text_auto='0.2s')
)

fig.update_yaxes(categoryorder = 'max ascending')

fig.show()

Question 4:¶

Thus far we looked at data from one year (2007). Lets create an animation to see the population growth of the continents through the years

In [6]:
df = px.data.gapminder()
df_continent_new = df.groupby(['continent', 'year'], as_index = False)['pop'].sum()
fig = px.bar(df_continent_new, x="pop", y='continent', color = 'continent',animation_frame="year", animation_group="continent", range_x=[0,4000000000])

#fig["layout"].pop("updatemenus")
fig.show()

Question 5:¶

Instead of the continents, lets look at individual countries. Create an animation that shows the population growth of the countries through the years

In [7]:
df = px.data.gapminder()
df_continent_new = df.groupby(['country', 'year'], as_index = False)['pop'].sum()
fig = px.bar(df_continent_new, x="pop", y='country', color = 'country',animation_frame="year", animation_group="country", range_x=[0,4000000000])

fig.update_yaxes(categoryorder = 'max ascending')
fig.show()

Question 6:¶

Clean up the country animation. Set the height size of the figure to 1000 to have a better view of the animation

In [8]:
df = px.data.gapminder()
df_continent_new = df.groupby(['country', 'year'], as_index = False)['pop'].sum()
fig = px.bar(df_continent_new, x="pop", y='country', color = 'country',animation_frame="year",height=1000, animation_group="country", range_x=[0,4000000000])

fig.update_yaxes(categoryorder = 'max ascending')
fig.show()

Question 7:¶

Show only the top 10 countries in the animation

Hint: Use the axis limit to set this.

In [9]:
df = px.data.gapminder()
df_continent_new = df.groupby(['country', 'year'], as_index = False)['pop'].sum()
n = len(df.country.unique())
fig = px.bar(df_continent_new, x="pop", y='country', color = 'country',animation_frame="year",height=1000,range_y=[n-10,n],animation_group="country", range_x=[0,4000000000])

fig.update_yaxes(categoryorder = 'max ascending')
fig.show()